Latency-driven Parallel Task Data Offloading in Fog Computing Networks for Industrial Applications

Mithun Mukherjee, Suman Kumar, Constandinos X. Mavromoustakis, George Mastorakis, Rakesh Matam, Vikas Kumar, Qi Zhang

    Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review


    Fog computing leverages the computational resources at the network edge to meet the increasing demand for latency-sensitive applications in large-scale industries. In this article, we study the computation offloading in a fog computing network, where the end users, most of the time, offload part of their tasks to a fog node. Nevertheless, limited by the computational and storage resources, the fog node further simultaneously offloads the task data to the neighboring fog nodes and/or the remote cloud server to obtain the additional computing resources. However, meanwhile, the offloaded tasks from the neighboring node incur burden to the fog node. Moreover, the task offloading to the remote cloud server can suffer from limited communication resources. Thus, to jointly optimize the amount of tasks offloaded to the neighboring fog nodes and communication resource allocation for the offloaded tasks to the remote cloud, we formulate a latency-driven task data offloading problem considering the transmission delay from fog to the cloud and service rate that includes the local processing time and waiting time at each fog node. The optimization problem is formulated as a quadratically constraint quadratic programming. We solve the problem by semidefinite relaxation. The simulation results demonstrate that the proposed strategy is effective and scalable under various simulation settings.

    Original languageEnglish
    Article number8918450
    JournalIEEE Transactions on Industrial Informatics
    Pages (from-to)6050-6058
    Number of pages9
    Publication statusPublished - 2020


    • Computation offloading
    • Industrial IoT
    • fog computing
    • latency sensitive
    • mobile edge computing
    • offloading decision
    • resource allocation


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